JPEG 2000: Image Compression Fundamentals, Standards and Practice
JPEG 2000: Image Compression Fundamentals, Standards and Practice
Adaptive Wavelet Filter Design for Optimized Image Source Encoding
ITCC '03 Proceedings of the International Conference on Information Technology: Computers and Communications
How Do Image Statistics Impact Lossy Coding Performance?
ITCC '00 Proceedings of the The International Conference on Information Technology: Coding and Computing (ITCC'00)
A Theoretical Framework for End-to-End Video Quality Prediction of MPEG-based Sequences
ICNS '07 Proceedings of the Third International Conference on Networking and Services
Quantified PQoS assessment based on fast estimation of the spatial and temporal activity level
Multimedia Tools and Applications
Distortion estimators for bitplane image coding
IEEE Transactions on Image Processing
On the performance of linear phase wavelet transforms in low bit-rate image coding
IEEE Transactions on Image Processing
A bit allocation method based on picture activity for still image coding
IEEE Transactions on Image Processing
JPEG2000 encoding with perceptual distortion control
IEEE Transactions on Image Processing
Analysis and architecture design of block-coding engine for EBCOT in JPEG 2000
IEEE Transactions on Circuits and Systems for Video Technology
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A compression quality prediction model is proposed for grey images coding with JPEG2000. With this model, the compression quality (PSNR) could be estimated according to the given compression ratio (CR) and the image activity measures (IAM) without coding images. The image activity measure is the weighted sum of the IAM values based on the 1-pixel-distance and 2-pixel-distance gradients along horizontal and vertical directions. We have shown that IAM is a function of the image variance and autocorrelation coefficients. Based on Shannon's rate-distortion theorem, a theoretical justification is provided for the correlation of IAM with PSNR. Experimental results show that the prediction error is lower than 1 dB for more than 70% sample images when CR is higher than 15. The prediction error is less than 2 dB for over 90% images. This prediction performance is acceptable for general applications.